Wuu, Joanne

Importance Classifying disease based on underlying pathobiology rather than clinical phenotype has implications for the development of biomarkers and therapy development. Observations Transactive response DNA-binding protein 43 kDa (TDP-43) pathology is observed across a range of clinically defined neurodegenerative disorders including limbic predominant age-related encephalopathy (LATE), most cases of amyotrophic lateral sclerosis (ALS), inclusion body myositis, multisystem proteinopathy, and approximately half the cases of frontotemporal dementia (FTD). Despite this shared biology, the current nosology for these neurodegenerative disorders is based on their distinct clinical phenotypes. An alternative approach recognizes the central role of TDP-43 pathology in disease pathogenesis, reserving the use of clinical terms like ALS, FTD, or LATE to describe phenotypic manifestations of underlying pathobiology. This approach also recognizes the converging biomarker and neuropathological data indicating that pathology begins presymptomatically, before the overt clinical manifestations of disease appear. Conclusions and Relevance In proposing a pathobiological definition of disease, the goal is to provide a road map for developing biomarkers that accurately reflect the underlying pathobiology of disease and for advancing therapeutic candidates that effectively target fundamental disease mechanisms.

Abstract Although sequencing costs have steadily decreased with advances in technology, they remain high for large scale studies. The design of traditional individual-disease sequencing studies is either case only or cases with relatively few controls, resulting in potential loss of statistical power for discovery of disease associated genes. Here we show that for a given number of sequenced cases, a large control sample size is critical to maximize power for rare variant burden analysis. Furthermore, we have developed an end-to-end workflow based tool (CoCoRV-nf) to facilitate the use of external biobank sequence resources as controls. The modules include consistent variant QC, variant annotation, ancestry population prediction, and gene based burden analysis using summary genotype information, and combined analysis from multiple independent results. The tool supports exomes and genomes from gnomAD and All of Us as controls with preprocessed datasets. We apply the tool in two rare neurological diseases: amyotrophic lateral sclerosis and neuroblastoma. For each disease, two case cohorts are paired with gnomAD and All of Us data, respectively, followed by a combined analysis. Not only did we recapture known genes, but also, we identified new candidate genes for both diseases. By leveraging multiple large external biobank sequence data, we demonstrate the feasibility of using our tool to maximize statistical power to identify new disease predisposition genes.

Abstract The idea that it might be possible to prevent some forms of amyotrophic lateral sclerosis and frontotemporal dementia has finally come of age. The hexanucleotide repeat expansion in the C9orf72 gene accounts for ∼10% of all amyotrophic lateral sclerosis and 10%–15% of all frontotemporal dementia diagnoses, with the two clinical syndromes co-manifesting in a significant number of patients. As a result, clinically unaffected carriers of pathogenic C9orf72 repeat expansions are currently the largest identifiable population at significantly elevated risk for both amyotrophic lateral sclerosis and frontotemporal dementia, and in whom it might be possible to prevent the emergence of clinically manifest disease. Strategies for the design of disease prevention trials among clinically unaffected C9orf72 carriers have begun to emerge separately in the amyotrophic lateral sclerosis and frontotemporal dementia fields. However, recognition of the need to define neurodegenerative diseases based on biology underscores the need to consider all potential clinical manifestations of a C9orf72 repeat expansion together, rather than the traditional siloed approach of focusing on only amyotrophic lateral sclerosis or only frontotemporal dementia. Indeed, emerging clinical and biological markers that might be used to quantify pre-symptomatic disease progression and to predict the short-term risk of phenoconversion to clinically manifest disease are shared across the phenotypic spectrum. Given the anticipated progress in the development of therapeutic strategies to target the C9orf72 repeat expansion, and the enthusiasm for prevention trials among the unaffected C9orf72 repeat expansion carrier population, now is the time to begin work on the design of disease prevention trials. To this end, The Association for Frontotemporal Degeneration and The ALS Association supported a multi-stakeholder workshop (in Washington D.C., June 2024) to unify efforts to design a prevention trial for the population at elevated genetic risk for the phenotypic spectrum of C9orf72 disease. Here we describe recommendations emanating from this workshop for the selection of outcome measures, delineation of eligibility criteria, optimal use of biomarkers and digital health technologies, potential analytic frameworks and relevant regulatory considerations related to C9orf72 disease prevention trials. We also emphasize the importance of the amyotrophic lateral sclerosis and frontotemporal dementia communities working together in partnership with the C9orf72 repeat expansion carrier community, the regulatory authorities and the broader drug development community.

Abstract Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer’s disease based on inferred underlying histopathology. Parkinson’s disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington’s disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned—more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers—we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.

Abstract Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

As potential treatments for C9ORF72‐associated amyotrophic lateral sclerosis (c9ALS) approach clinical trials, the identification of prognostic biomarkers for c9ALS becomes a priority. We show that levels of phosphorylated neurofilament heavy chain (pNFH) in cerebrospinal fluid (CSF) predict disease status and survival in c9ALS patients, and are largely stable over time. Moreover, c9ALS patients exhibit higher pNFH levels, more rapid disease progression, and shorter survival after disease onset than ALS patients without C9ORF72 expansions. These data support the use of CSF pNFH as a prognostic biomarker for clinical trials, which will increase the likelihood of successfully developing a treatment for c9ALS. Ann Neurol 2017;82:139–146